AI-driven autonomous agents that handle your most repetitive processes end-to-end — so your team can focus on what matters.
Automations / Agentic Workflows
An agent is different from an automation: it carries a whole process rather than one step, and it decides rather than merely executes. That is genuinely powerful for work that is repetitive but not identical every time — qualifying a lead, chasing a sequence of follow-ups, producing a first draft. It is also where most projects come unstuck, which is why every agent we build starts with what it may touch, what it must escalate, and where a person signs off.
Get startedAn agent differs from an automation in that it carries a whole process rather than one step — deciding, not just executing. That is genuinely powerful for work that is repetitive but not identical every time. It is also where most projects come unstuck, because an agent given a vague job and no oversight produces confident nonsense at scale.
of day-to-day work decisions will be made autonomously through agentic AI by 2028, from effectively none in 2024
Gartner, 2025
of enterprise software will include agentic AI by 2028, up from under 1%
Gartner, 2025
of agentic AI projects are forecast to be cancelled before the end of 2027
Gartner, June 2025
We work out whether the process wants an agent at all. Plenty of them want a deterministic automation and will work better, cheaper and more predictably that way — we will say so.
What the agent may access, what it has to hand to a person, what it logs. The boundaries get designed before the behaviour, not bolted on after something goes wrong.
It shows what it would have done, against real work, for as long as it takes you to trust it. Only then does it act, and only within the scope you agreed.
An agent that takes a job from start to finish — reading the enquiry, deciding what it is, drafting the response, updating the record and raising the next task — rather than automating one link and handing the rest back.
A written scope of what it can touch, hard rules on what must be escalated, and a full log of every action. This is the part that separates an agent that keeps working from one that gets switched off.
Anything that reaches a customer, moves money or changes a commitment can be held for approval. You choose which categories ever run unattended, and you can change your mind.
Before it does anything, it shows you what it would have done against real work. You see the accuracy on your own processes rather than in a demo built to succeed.
Agents drift as the business changes around them. We watch what yours is doing, report on where it is being overridden, and adjust — because an unmonitored agent is a liability with a subscription.
Describe it and we’ll tell you honestly whether it wants an agent, a plain automation, or neither. That answer is free, and it is frequently the cheapest option.
That third figure is the important one. Most failed agent projects were processes that wanted a deterministic automation and got a language model instead. We scope for the boring answer first and only reach for an agent where the judgement is genuinely needed.
What it may touch, what it must escalate, what it logs, and where a human signs off. Agents that run unattended from day one are the ones that end up in that cancellation statistic.
Every agent we build goes through a period of showing what it would have done, against real work, before it is allowed to do anything. You see the accuracy on your own processes rather than in a vendor demo.
An automation follows a fixed path: this happens, so do that. An agent is given an objective and works out the steps, which means it can handle work that varies. The practical test is whether the process needs judgement — if the rules can be written down completely, you want an automation, because it is cheaper, faster and entirely predictable. We reach for an agent only where the variation is real, and we will happily talk you out of one.
By not giving it the opportunity, and by watching before trusting. Every agent gets an explicit scope of what it may access and hard rules on what must be escalated to a person, and it runs in shadow mode — showing what it would have done, against real work — until you are satisfied. Anything customer-facing or financial can stay behind approval permanently. Gartner expects over 40% of agentic projects to be cancelled by the end of 2027, and the ones that fail are overwhelmingly the ones that skipped this.
No, and the distinction matters commercially. A chatbot answers; an agent acts — it reads your systems, updates records, raises tasks and moves a process forward. The value is not in the conversation, it is in the work that no longer needs a person to shepherd it. That also means the integration work underneath is most of the build, which is why agents delivered as a plug-in rarely amount to much.
Book a free discovery call and we’ll identify the workflows that will save you the most time.
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